uq in python - intro · uq in python - intro andré r. brodtkorb, associate professor, oslo...
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UQ IN PYTHON - INTROAndré R. Brodtkorb, Associate Professor, Oslo Metropolitan UniversityResearcher SINTEF Digital
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• Robert Millikan held a famous experiment published in 1910.
• Part of the reason for his 1923 Nobel prize in physics
• By varying the charge of the electric field, the (charged) oil particles would rise or fall.
• Millikan discovered that that charge was discrete, and had a value of 1.5924(17)×10−19 coulomb with a very small margin of error
• The value is today believed to be 1.602176487(40)×10−19 coulomb2
Measuring the charge of an electron
Oil-drop experiment image, CC-BY-SA 3.0, Theresa Knott
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Measuring the charge of an electron
Beauty
Publish this surelyBeautiful!!
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• Millikan had almost exactly the correct value, but extremely small error margins in published result.
• A lot of data excluded from publication
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Measuring the charge of an electron
Figure by David Schneider
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Source: • Tenfold increase in scientific research papers retracted for fraud, Alok Jha, The Guardian, Monday 1 October 2012
• Drug development: Raise standards for preclinical cancer research, C. Glenn Begley and Lee M. Ellis, Nature 483, 2012
Tenfold increase in scientific research papers retracted for fraud since 1975: Two thirds retracted for scientific misconduct, not error
Findings in six of 53 landmark studies in cancer research can be confirmed
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A chemist treats the laboratory with thorough respect, having strict securityprocedures, careful note taking during experiments, etc. So should we also treatour computers, as it is the laboratory of computational science.
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Working reproducibly should become a central part of youreveryday work cycle: it is not enough to think of it as a postpublication step (which never happens, anyway…)
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"In academia, software quality, user interfaces,documentation, testing and reproducibility, will all be
sacrificed at the altar of publications"
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Python and Jupyter Notebooks
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Python
• Almost 30 years old!
• Two "versions"• "Jurassic" version 2.7
• Modern version 3.x
• Mostly compatible with each other
• Runs on everything from cellphones to supercomputers
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Python ecosystem
• Mature and fast libraries
• Numpy – matrices and arrays in Python
• Pandas – statistics and data analysis
• Scikit-learn – Machine learning (see 2018 winter school!)
• Matplotlib – interactive plotting similar to Matlab
• Mayavi – 3D interactive visualization
• …
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Jupyter Notebook
• Major part of 2013 Geilo Winter School on Reproducible Research
• Makes Python interactive (what Julien is using)
• REPL environmentRead-Eval-Print-loop
• Interactive prototyping workbench11
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Exercise 1: Plot unit circle• Unit circle: y = +/- sqrt(1 – x^2)
• import numpy as npfrom matplotlib import pyplot as plt
• Generate x as a linear space (linspace) in numpy
• Use sqrt from numpy to generate y
• Use plt.plot(x, y, 'r.-') to plot
• Use question mark (?) to get help on commands!
• Add legend, change plot color, line type, add marker12
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Exercise 2: Monte Carlo integration of Pi
• Sample n random points in 2d (np.random.random)
• Estimate area of circle, and use pi = A / r^2
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Teknologi for et bedre samfunn